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Multi-Armed Bandits

1,057 papers

Papers per year

5
27
87
38
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Papers

Provably Optimal Algorithms for Generalized Linear Contextual Bandits ICML 2017
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons ICML 2017
Identifying Best Interventions through Online Importance Sampling ICML 2017
Safety-Aware Algorithms for Adversarial Contextual Bandit ICML 2017
Model-Independent Online Learning for Influence Maximization ICML 2017
Learning a Ground Truth Ranking Using Noisy Approval Votes IJCAI 2017
Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits IJCAI 2017
Optimal Posted-Price Mechanism in Microtask Crowdsourcing IJCAI 2017
Crowd Learning: Improving Online Decision Making Using Crowdsourced Data IJCAI 2017
Context Attentive Bandits: Contextual Bandit with Restricted Context IJCAI 2017
Thresholding Bandits with Augmented UCB IJCAI 2017
Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces IJCAI 2017
XOR-Sampling for Network Design with Correlated Stochastic Events IJCAI 2017
Perishability of Data: Dynamic Pricing under Varying-Coefficient Models JMLR 2017
Online Learning to Rank with Top-k Feedback JMLR 2017
Threshold Bandits, With and Without Censored Feedback NIPS 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution NIPS 2016
Refined Lower Bounds for Adversarial Bandits NIPS 2016
Tracking the Best Expert in Non-stationary Stochastic Environments NIPS 2016
Regret of Queueing Bandits NIPS 2016
Online Pricing with Strategic and Patient Buyers NIPS 2016
Optimistic Gittins Indices NIPS 2016
Multiple-Play Bandits in the Position-Based Model NIPS 2016
Double Thompson Sampling for Dueling Bandits NIPS 2016